Gut microbiota functions - metabolism of nutrients and other food

components

1

Ian Rowland

Department of Food & Nutritional Sciences

University of Reading

Co-authors

• Glenn Gibson (University of Reading)

• Kieran Tuohy (FEM-IASMA)

• Jeremy Nicholson (Imperial College London)

• Karen Scott (Rowett Institute/University of Aberdeen)

• Jonathan Swann (Imperial College London)

2

Gut microbiota interaction with host

Digestive

function

Cancer

Obesity

AAD

Metabolism

Metabolic

syndrome/Diabetes

IBS/IBD

Immune

system

4

• Firmicutes

– Clostridium

– Roseburia

– Faecalibacterium

– Blautia

– Dorea

– Lactobacillus

– Peptostreptococcus

– Eubacterium

– Streptococcus

– Staphylococus

– Butyrivibrio

• Archaea

– Methanobrevibacter

• Fusobacteria

Human gut microbiota – Main phyla & genera • Bacteroidetes

– Bacteroides

– Prevotella

• Verrucomicrobia

– Akkermansia

• Proteobacteria

– Escherichia

– Klebsiella

– Desulfovibrio

• Actinobacteria

– Bifidobacterium

– Collinsella

90% of bacteria are in

Bacteroidetes/Firmicutes phyla

Human vs mouse microbiota

5

• Extrapolating results from mice with regard to

microbiota metabolism and human health is not

straightforward

– Many differences at the level of specific genus/species

abundances (Nguyen T et al Disease Models & Mechanisms 8:1-16. 2015)

– Distribution of microbiota different

• But – much of the evidence that gut microbes play a

role in metabolism and human health comes from

studies in mice especially comparing germ free vs

conventional mice

Aims of the review

• To review the mechanisms and pathways involved in

gut microbial metabolism of dietary components

• To review the literature on the types of

microorganisms involved in GI metabolism of dietary

nutrients and non-nutrients

• To consider the methodologies for investigating gut

microbiota metabolism

6

Dietary components reviewed

• Carbohydrates

• Proteins

• Fats

• Vitamins

• Phytochemicals/polyphenols

• Bile acids

7

Methodologies

• Isolated cultures

• Gut microbial enzyme activity

• Mathematical modeling

• System biology approaches

– Metagenomics

– Metatranscriptomics

– Metaproteomics

– Metabonomics

8

Carbohydrate fermentation

Polysaccharides Oligosaccharides Mucin Microbial metabolism

Breath Flatus

Transported in

blood to

peripheral

tissues,

lipogenesis

Gluconeo-

genesis

in the liver;

satiety

signalling

Major energy

source

for human

colonocytes;

Protects

against cancer

Faeces

H2, CO2, H2S, CH4

Acetate

Propionate Butyrate

Biomass

© Glenn Gibson/

Karen Scott

Fermentation by main bacterial phyla

Numerical Functional importance Example importance Firmicutes 60% Cluster XIVa (25%) butyrate production E.rectale Cluster IV (25%) polysaccharide utilisation F. prausnitzii Roseburia bromii Cluster IX (10%) propionate production Megasphaera Bacteroidetes 25% wide range of substrates utilised acetate, succinate, propionate Bacteroides produced Actinomycetes 10% Oligosaccharide users Bifidobacteria prime/modulate immune response lactate production Others 5% lactic acid bacteria Lactobacilli sulphate reducing bacteria Desulfovibrio © Karen Scott mucin degraders

Sulphate-reducing bacteria

• Occur in 45% of healthy persons

• Reduce sulphate to sulphide, in

conjunction with an electron donating

substrate

• Compete with methanogens for

hydrogen

• Commonest genus is Desulfovibrio

• Pathological role in the gut remains

unclear

© Glenn Gibson

Methanogens

• Archae that produce methane as a

metabolic byproduct

• Obligately require hydrogen

• There are over 50 species of

methanogens, but only a few isolated

from the gut so far

• Very difficult to cultivate

© Glenn Gibson

Protein fermentation

Microbial metabolism

Blood Faeces

Urine

Blood Faeces Urine

Ammonia Amines Phenols

Branched-chain fatty acids (i-Val,

i-But, i-Cap)

clostridia

peptostreptococci

peptococci

COLON

LIVER

GUT mucosa

tyrosine

4-cresol

4-cresyl

sulfate (4CS)

phenylalanine

phenylacetate

phenylacetylglutamine (PAG)

glutamine

Microbiome / Genome

© Jon Swann

Lipid metabolism

15

Proposed pathways of LA metabolism by bacterial species

isolated from the human gut.

Devillard et al. J. Bacteriol. 2007;189:2566-2570

Linoleic acid metabolism

Metabolite Species

OH 18:1 FA Lact. reuteri, lactis; Prop.thoenii,

(HFA) Bif. adolescentis, infantis; F. praunitzii;

Roseburia intestinalis*, faecis*

CLA Prop. freudenreichii; Bif. breve

VA Roseburia inulinivorans*, hominis*;

Butyrivibrio fibrisolvens

* 76-100% conversion in vitro

Isolated strains did not produce stearic acid, only faecal slurries

17

Devillard et al. J. Bacteriol. 2007;189:2566-2570

Vitamin synthesis

• Studies in GF & CV animals and in Ab treated humans

indicate microbiota can synthesize certain vitamins

• Metagenomic studies show vitamin synthesis genes are

common esp.vitamin K and B group vitamins - biotin,

cobalamin, folate, nicotinic acid, panthotenic acid,

pyridoxine, riboflavin and thiamine

• For riboflavin & biotin, all tested microbes in Bacteroidetes

Fusobacteria and Proteobacteria phyla had required

pathways, fewer Firmicutes and Actinobacteria had the

pathways

• Bacteroidetes seem to be most important phyla for vitamin

synthesis

• Many of vitamins are utilized by other bacteria

18

Bile acids

Bile salt hydrolase

• BSH genes have been identified in the main bacterial

genera including Bacteroides, Bifidobacterium,

Clostridium, Lactobacillus, and Listeria

• Most hydrolyze both glyco and tauro-conjugates.

• Reduces toxicity of bile acids and releases nitrogen,

sulphur and carbon atoms

19 Jon Swann

BILE ACIDS

7a-dehydroxylation

Deconjugation by bacterial

bile salt hydrolases (BSH)

Ursodeoxycholic acid

Epimerization

Lipid digestion:

– Deconjugation reduces efficiency of bile acids for emulsification

of dietary lipids and micelle formation

– CA greater than CDCA and DCA at emulsifying lipids

– Gut microbial BSH expression altered plasma bile acid signature

and transcription of genes involved in fat metabolism and

metabolic signaling pathways (Joyce 2014)

© Jon Swann

Bile acids – microbes involved

Gerard, Pathogens. 2014 3: 14–24.

21

Phytochemicals

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Polyphenols

Polyphenols

• Often poorly absorbed in small intestine

colon

• Studies in GF and human microbiota-

associated animals and in vitro faecal

incubations show parent polyphenols are

extensively metabolized by the microbiota,

(deglycosylation, ring fission, dehydroxylation)

- can impact bioactivity

23

Gut microbiota & inter-individual

variation in polyphenol metabolism

• Differences in composition of microbiota between

individuals can have significant effects on extent of

metabolism, metabolite profile & bioavailability

• Examples:

– Isoflavonoids (daidzein to equol)

– Naringin

– Anthocyanins

– Lignans

– Tea catechins

– Rutin

24

Polyphenol metabolism –

microbes involved

Often requires involvement of a range of

microbes.

Example: secoisolariciresinol diglucoside

25

Secoisolariciresinol diglucoside and its gut bacterial metabolites.

Methodologies

• Isolated cultures

• Gut microbial enzyme activity

• Mathematical modeling

• System biology approaches

– Metagenomics

– Metatranscriptomics

– Metaproteomics

– Metabonomics

27

Isolated cultures

• Equol production: Serially dilute faecal sample from

equol producer onto agar, test single colonies for

equol production – yielded a 4-member consortium

(Decroos et al 2005)

• Enrichment culture – used for isolating CHO

degraders from ruminants. Continuous culture

fermenters containing medium with eg xylan as sole

CHO source, run for 8 weeks then samples plated

onto xylan agar. Identified complex communities

capable of metabolism (Ziemer 2014)

28

Enzyme activities

• Measure specific enzyme activity in faecal samples eg

glucosidases, polysaccharidases, reductases. Ignores

individual organisms.

• Assay enzymes in gut bacterial isolates representing

major microbiota types to identify main organisms

involved. Glucuronidase activity mostly associated

with clostridial clusters, glucosidase with bifids and

bacteroides

• Limitation – activity in vitro may not reflect in vivo

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Gut microbiota - metabolism

• Reduction – C=C bonds

– Azo links

– NO3/NO2

– Aldehydes

– sulphates

• Hydrolysis – Glycosides

– Glucuronides

– Sulphates

– Esters

– Amides

30

• Dehydroxylation (C & N)

• Methylation

• Demethylation

• Nitrosation

• Deamination

• Ring fission

• Aromatization

• oligomer breakdown

• Polysaccharide fermentation

Mathematical modeling

• Muñoz-Tamayo 2011: Kinetic modelling showed the

role of bacterial cross-feeding in conversion of lactate

to butyrate by two human gut bacteria, Eubacterium

hallii and Anaerostipes coli.

• Kettle 2014-15: Minimal model of the intestinal

ecosystem, 10 bacterial functional groups. Used to

estimate the effect of removing entire functional

groups (or single strains within a functional group) on

the community profile and activity. Potential for

assessing consequences of dysbiosis on development

of disease.

31

32

© Karen Scott

Summary of interactions between

functional groups in model

From Kettle et al 2014. Env Microbiol doi:10.1111/1462-2920.12599

• Multivariate

• Hypothesis-

generating

• Model-building to

understand complex

systems

Top-down approach

Bottom-up approach • Hypothesis-led • Uni- or bi-variate

Systems Biology aproaches

Systems biology approaches

are ideally suited to study

the microbiome due to its

complexity and its

interactions with host © Jon Swann

Systems biology approaches

• Metagenomics – study functional genes associated with

specific microbial types,

• Meta-transcriptomics – monitor active bacteria, reveals

functional roles (eg CHO metabolism) info on functional

dysbiosis,

• Meta-proteomics – confirming microbial function (faecal

meta proteome is subject-specific and stable, protein

biomarkers)

• Metabonomics – pathway analysis, metabolic biomarkers of

disease risk eg high fecal bile acid, lower bc SCFA in IBS

(Gall et al J Proteome Res 10, 4208 2011)

35

Metagenomics applications

• Used to study changes in microbial function in disease

states

• Distribution of BSH genes in microbiota, high level of

redundancy

• Distribution and diversity of carbohydrate active

enzymes (CAZymes) in microbiota

36

Metatranscriptomics applications

• Identification of the most metabolically active microbial

groups

• Most active Firmicutes : Lachnospiraceae and

Ruminococcaceae

• Most active Bacteroidetes: Bacteroidaceae,

Prevotellaceae, Rickenellaceae

• Main activities :carbohydrate transport and

metabolism, energy production and conversion,

synthesis of cellular components

• Less important: amino acid and lipid metabolism, cell

motility, secondary metabolite biosynthesis

37

Metaproteomics applications

• Few studies, small subject numbers (~3)

• Some evidence that faecal metaproteome is subject

specific and stable over 1 year. Core of ~1000 proteins

• Main functional categories - metabolism of

carbohydrates, nucleotides, energy, and vitamins (B12

and folic acid).

• Can link proteins to taxonomic groups insight into

microbes at species/strain level involved in specific

catalytic functions and pathways i.e. genotype-

phenotype linkages

38

Metaproteomic vs metagenomic analyses Verberkmoes et al 2009 39

Metagenome

Metaproteome

Metabonomics

• Measure metabolites in host samples that derive

directly from the microbiome a direct read-out of gut

microbial activity.

• If absorbed from the gut, microbial products can

interact with host metabolic processes resulting in

downstream metabolic perturbations and the

generation of microbial-host co-metabolites, all of

which can be captured by metabolic profiling.

40 © Jon Swann

Metabonomics – typical strategy

41 © Jon Swann

Limitations

• Methodology – need for harmonization/standardization

to provide reference protocols to enable comparisons

of different studies

– Identification of critical points influencing results ‘HACCP’

– Sample collection & storage

– Macromolecule extraction and processing

– Analytical methodologies

• Bioinformatics – complex and developing, especially

for integrating data from different omics

• Reference databases limited

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Conclusions

• Gut microbiota metabolism extends metabolic flexibility of

host to process wide range of substrates

• CHO metabolism major function of microbiota – pathways

well studied

• Large amount of functional redundancy so composition

variation may not result in functional variation

• Need for consensus on best ‘markers’ of microbial

metabolism

• ‘Omics’ provide insight into microbiota function at high

resolution

• In future important to integrate omics datasets to fully

exploit potential and develop mathematical models

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Integration of omics

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• sample processing & preservation: homogenization with RNAlater followed by centrifugation steps before

snap-freezing

cryomilling of cell pellets and solvent extraction of the intracellular polar and non-polar metabolite fractions

Physicochemical biomacromolecular isolation

Roume et al ISME 7,110-121

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